Methods and systems for augmentative and alternative communication

ABSTRACT

Methods and systems for augmentative and alternative communication are disclosed. An example method can comprise receiving a candidate input, classifying the candidate input as an intentional input, and generating a signal in response to the intentional input.

CROSS REFERENCE TO RELATED PATENT APPLICATIONS

This application is a Continuation of U.S. application Ser. No.15/409,004, filed Jan. 18, 2017, which is a Continuation of U.S.application Ser. No. 14/993,889, filed Jan. 12, 2016, and issued as U.S.Pat. No. 9,595,171, on Mar. 14, 2017, which claims priority toInternational Application No. PCT/US2014/046356 with an internationalfiling date of Jul. 11, 2014, which claims priority to U.S. ProvisionalApplication No. 61/845,673, filed Jul. 12, 2013, all of which are hereinincorporated by reference in their entireties.

BACKGROUND

Current hospital accreditation standards mandate that all patients beprovided with the means to summon the assistance of caregivers (e.g.nurse call). Many critical care patients are too weak to activatestandard or alternative nurse call switches that are available at mostfacilities. Mechanical ventilation further limits patients to use voiceto summon or communicate with caregivers. For many patients in intensivecare and long term acute care settings, there are no existingcommunication methods that can transduce the minimal intentionalgestures that these patients are capable of making. These and othershortcomings are addressed in the present disclosure.

SUMMARY

It is to be understood that both the following general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive, as claimed. Provided are methods and systemsfor augmentative and alternative communication. An example method cancomprise receiving a candidate input, classifying the candidate input asan intentional input, and generating a signal in response to theintentional input.

Another example method can comprise receiving a candidate input. Thecandidate input can be classified as an intentional input. One or moredevices associated with the intentional input can be determined. Asignal can be generated to control the one or more devices associatedwith the intentional input.

An example apparatus can comprise an input interface, an outputinterface, a memory and a processor coupled to the input interface, theoutput interface, and the memory. The input interface can be configuredfor receiving a candidate input from one or more sensors. The outputinterface can be configured for transmitting a signal to a controlleddevice. The memory can be configured for storing a filter. The processorcan be configured to classify the candidate input received by the inputinterface by applying the filter stored in the memory, and providing thesignal to the output interface for transmission to the controlleddevice.

Additional advantages will be set forth in part in the description whichfollows or may be learned by practice. The advantages will be realizedand attained by means of the elements and combinations particularlypointed out in the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments and together with thedescription, serve to explain the principles of the methods and systems:

FIG. 1 is an exemplary apparatus capable of performing the methodsdisclosed;

FIG. 2A illustrates average spectrum of a tongue click in frequencydomain;

FIG. 2B illustrates signal intensity of tongue click in time domain;

FIG. 2C illustrates average spectrum of fan noise and tongue clicks infrequency domain;

FIG. 2D illustrates signal intensity of fan noise and tongue clicks intime domain;

FIG. 2E illustrates average spectrum of a filtered tongue click and fannoise in frequency domain;

FIG. 2F illustrates signal intensity of a filtered tongue click and fannoise in time domain;

FIG. 3 is block diagram illustrating an audio signal detection method;

FIG. 4A illustrates an example apparatus using analog filtering;

FIG. 4B illustrates an example apparatus using digital filtering;

FIG. 5 illustrates the logic of a signal detection algorithm;

FIG. 6 is a flow chart illustrating an exemplary method;

FIG. 7 is a flow chart illustrating an exemplary method;

FIG. 8 is exemplary apparatus;

FIG. 9 is exemplary system;

FIG. 10 is exemplary operating environment;

FIG. 11A shows a top-down perspective view of an example apparatus and aclamp;

FIG. 11B shows a bottom-up perspective view of the example apparatus andthe clamp;

FIG. 11C shows a side-view of the example apparatus and the clamp;

FIG. 11D shows another side-view of the example apparatus and the clamp;

FIG. 12A shows an example sensor mounting;

FIG. 12B shows an another example sensor mounting;

FIG. 12C shows an another example sensor mounting;

FIG. 12D shows an another example sensor mounting;

FIG. 13A illustrates an example apparatus with an pole mounted speechgenerating device;

FIG. 13B illustrates an example user interface provided by the display;

FIG. 13C shows another view of the mounting device and display device;

FIG. 14 is a block diagram illustrating an example apparatus;

FIG. 15 is a block diagram illustrating another example apparatus;

FIG. 16 is a block diagram of an apparatus illustrating aspects of anexample sensor recognition switch;

FIG. 17 illustrates an example processing unit of the apparatus;

FIG. 18 illustrates an example power management system;

FIG. 19 is a flow chart illustrating an example method for managing adevice;

FIG. 20 is a flow chart illustrating an example method for recognizing agesture; and

FIG. 21 is a flow chart illustrating an example method for recognizing agesture.

DETAILED DESCRIPTION

Before the present methods and systems are disclosed and described, itis to be understood that the methods and systems are not limited tospecific methods, specific components, or to particular implementations.It is also to be understood that the terminology used herein is for thepurpose of describing particular embodiments only and is not intended tobe limiting.

As used in the specification and the appended claims, the singular forms“a,” “an” and “the” include plural referents unless the context clearlydictates otherwise. Ranges may be expressed herein as from “about” oneparticular value, and/or to “about” another particular value. When sucha range is expressed, another embodiment includes from the oneparticular value and/or to the other particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms anotherembodiment. It will be further understood that the endpoints of each ofthe ranges are significant both in relation to the other endpoint, andindependently of the other endpoint.

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where said event or circumstance occurs and instances where itdoes not.

Throughout the description and claims of this specification, the word“comprise” and variations of the word, such as “comprising” and“comprises,” means “including but not limited to,” and is not intendedto exclude, for example, other components, integers or steps.“Exemplary” means “an example of” and is not intended to convey anindication of a preferred or ideal embodiment. “Such as” is not used ina restrictive sense, but for explanatory purposes.

Disclosed are components that can be used to perform the disclosedmethods and systems. These and other components are disclosed herein,and it is understood that when combinations, subsets, interactions,groups, etc. of these components are disclosed that while specificreference of each various individual and collective combinations andpermutation of these may not be explicitly disclosed, each isspecifically contemplated and described herein, for all methods andsystems. This applies to all aspects of this application including, butnot limited to, steps in disclosed methods. Thus, if there are a varietyof additional steps that can be performed it is understood that each ofthese additional steps can be performed with any specific embodiment orcombination of embodiments of the disclosed methods.

The present methods and systems may be understood more readily byreference to the following detailed description of preferred embodimentsand the examples included therein and to the Figures and their previousand following description.

As will be appreciated by one skilled in the art, the methods andsystems may take the form of an entirely hardware embodiment, anentirely software embodiment, or an embodiment combining software andhardware aspects. Furthermore, the methods and systems may take the formof a computer program product on a computer-readable storage mediumhaving computer-readable program instructions (e.g., computer software)embodied in the storage medium. More particularly, the present methodsand systems may take the form of web-implemented computer software. Anysuitable computer-readable storage medium may be utilized including harddisks, CD-ROMs, optical storage devices, or magnetic storage devices.

Embodiments of the methods and systems are described below withreference to block diagrams and flowchart illustrations of methods,systems, apparatuses and computer program products. It will beunderstood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, respectively, can be implemented by computerprogram instructions. These computer program instructions may be loadedonto a general purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus create a means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the function specified in the flowchartblock or blocks. The computer program instructions may also be loadedonto a computer or other programmable data processing apparatus to causea series of operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of means for performing the specified functions,combinations of steps for performing the specified functions and programinstruction means for performing the specified functions. It will alsobe understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, can be implemented by special purposehardware-based computer systems that perform the specified functions orsteps, or combinations of special purpose hardware and computerinstructions.

Provided are methods and systems for augmentative and alternativecommunication. The disclosed methods and systems can process complexsignals embedded in complex noise in order to use the signals to allow apatient or user to control one or more devices in their environment,e.g. activating nurse call or patient controlled pain pumps, speechgenerating communication devices, and the like. In an aspect, thedisclosed methods and systems can improve signal interpretation for adiverse set of input devices (e.g., acoustic, pressure, proximity andreflectance) used for augmentative and alternative communication devicesfor a variety of users. An exemplary application can include patients ina hospital setting who are paralyzed or severely incapacitated. Themethods and systems provided can eliminate background noise (e.g., fromhospital equipment) and other environmental sources as well asnon-communication initiated movements from the patient (for example,normal eye blinks). The disclosed methods and systems can distinguishthe intentional gesture from the ambient noise received from theenvironment or from non-intentional tremor in the patient's gestures. Inan aspect, the methods and systems disclosed can be used in a hospitalenvironment to enable intubated and otherwise disabled patients tocommunicate with caregivers. The methods and systems can be used byother care facilities such as outpatient facilities and elderly carefacilities.

In an aspect, the disclosed methods and systems can comprise signalprocessing that can analyze the kinematics of intentional gestures thatcan be transduced and serve as inputs. For example, the methods cancomprise intentional input detection regardless of the input modality(e.g., audio, tactile, pressure, IR reflectance). For example, ratherthan responding each time a user touches a switch plate, a signalprocessing switch can effectively filter out the unintentional touchesand only respond to an intentional touch. This can be achieved byidentifying the intentional gesture based on characteristics of theintentional gesture in the frequency domain, the time domain, or both.

An exemplary apparatus 100, shown in FIG. 1, can comprise one or moresensor inputs 101 for sensors such as microphones, pressure bulbs,pressure transducers, and the like. These sensor inputs can be processedby a signal processor 102 to classify a specific stimulus asintentional, as distinguished from noise and unintentional stimuli. Theapparatus can be configured to a signal output 103 to control a device,which can be activated by the intentional stimulus and an optionalvisual output which can display to the user a menu of instructions andoptions. As an example, a controlled device can comprise one or more ofa nurse call switch, a computer, a television, a telephone, a medicaldevice, an application (e.g., iPad applications), a speech generatingdevice, and the like. In an aspect, the signal output 103 can be used toinvoke keyboard commands for communication or controlling othermechanical or computerized outputs. In an aspect, any type of sensor andany type of output can be utilized.

In an aspect, the methods and systems can be configured to operate inconjunction with a touch switch. A common problem with signals fromswitches activated by touch (either mechanical or capacitance/proximitydetector switches) is that in order to respond to gestures that generateminimal displacement and force, the sensors are so sensitive that theyare often activated unintentionally by tremors that often accompany theintentional gesture. A characteristic of the tremor can be determinedand processed to generate a filter. For example, a tremor can generate asignal from about 4 Hz to about 12 Hz, for example a 4 Hz, 5 Hz, 6 Hz, 7Hz, 8 Hz, 9 Hz, 10 Hz, 11 Hz, and/or 12 Hz signal. The disclosed methodsand systems can comprise applying a low pass filter to the signalreceived from a touch switch to account for the tremors. In an aspect,an intentional tremor can have a frequency of below about 5 Hz. Themethods and systems can then respond to the underlying intentionalgesture and not to any higher frequency signals received from thetransducer that are the consequence of the tremor in the gesture.

In an aspect, the methods and systems can be configured to operate inconjunction with a pressure sensor. For patients who cannot generateeither the force or displacement necessary to activate touch switches, apressure sensor can be used. Pressure sensors can be implemented as“sip-and-puff switches” used by individuals who are quadriplegic orparaplegic. These switches require that the user generate adequatechanges in oral pressure. For individuals who cannot generate the oralpressure needed to activate the “sip-and-puff switches,” one can use aclosed silastic bulb that only requires a lip closure or a bitinggesture. Such a bulb can be positioned just to the side of the user'smouth and a small lip gesture can allow the user to grasp the bulb andthus generate a positive pressure change.

However, many intubated or trached patients, who are also unable tomove, prefer to keep the silastic bulb in their mouths. A consequence ofthis is that the small inadvertent movements of the lips and tongue thatare not associated with the intentional gesture are also generatingpressure changes. The disclosed methods and systems can determine acharacteristic of the inadvertent movements and generate a filter toaccount for the inadvertent movements. For example, the methods andsystems can analyze a time course of lip gestures and magnitude of thepressure changes associated with an intentional gesture, therebygenerating a filter that can discriminate between intentional andunintentional inputs based on particular pressure changes over aparticular time interval.

In an aspect, the methods and systems can be configured to operate inconjunction with an infrared sensor, such as an infrared reflectanceswitch. For many spinal cord injury patients as well as patients withlocked-in-syndrome, the only motor gestures that they can reliablygenerate involve eyelid control. An eye-blink switch can be utilized todetect changes in reflected infrared light that are a consequence ofeyelid movements. A problem is that existing eye-blink switches havedifficulty distinguishing the reflectance changes associated with anintentional blink gesture from those associated with unintentional blinkgestures, such as natural blinks or slower lid movements associated witheither gaze shifts or lid dropping associated with drowsiness. Thedisclosed methods and systems can determine a characteristic of theintentional movements and generate a filter to account for theunintentional movements. In an aspect, the disclosed methods and systemscan use kinematic analysis of eyelid movements for blink detection whichis not responsive to the rapid reversal of reflectance associated with anatural blink, nor to the slower reflectance changes associated withslower involuntary lid movements. The methods and systems can settemporal cutoffs that only respond to the reflectance changes associatedwith the intermediate temporal duration of the intentional blink/wink.

In an aspect, the methods and systems can be configured to operate inconjunction with an audio sensor. For individuals who are able togenerate sound, a Schmidt-trigger circuit (e.g., Voice Switch, Clapperswitch) can be used. A problem with such a switch is that the switch canbe triggered by a wide range of sounds and are not responsive to just aparticular sound. As a result, there are many false positives and falsenegatives that result from variations in the audio signal intensity. Ina hospital environment, many patients attempt to get staff attention bygenerating “small mouth” sounds. These sounds are made by small tonguemovements or by popping of the lips. These are acoustically verylow-amplitude signals that are often buried in the ambient noise.Ambient noise can include, for example, noise generated by equipment inthe intensive care setting or by respiratory or gustatory soundsgenerated by the patient.

The disclosed methods and systems can determine a characteristic of theintentional movements and generate a filter to account for theunintentional movements. For example, the methods and systems can employan acoustic analysis of intentional sounds (e.g., the “small mouth”sounds) to determine a time domain and frequency domain signature. Thedisclosed methods and systems can apply a filter (e.g., digital filter,analog filter) to an audio signal picked up by an audio sensor in orderto identify intentional inputs. By way of example, FIGS. 2A-2Fillustrate signal and spectral characteristics of environmental noiseand a target mouth sound. Specifically, FIG. 2A illustrates averagespectrum of a tongue click in frequency domain. FIG. 2B illustratessignal intensity of tongue click in time domain. FIG. 2C illustratesaverage spectrum of fan noise and tongue clicks in frequency domain.FIG. 2D illustrates signal intensity of fan noise and tongue clicks intime domain. FIG. 2E illustrates average spectrum of a filtered tongueclick and fan noise in frequency domain. FIG. 2F illustrates signalintensity of a filtered tongue click and fan noise in time domain. Asshown in FIG. 2C and FIG. 2D, an intended tongue click is obscured by abackground noise that is not desired, for example, fan noise. Thesignals representing a tongue click and a fan noise added together canbe an input to a band-pass filter that would pass the characteristicfrequencies of an intended tongue click. The output signal of theband-pass filter is shown in FIG. 2E and FIG. 2F. By defining a filterthat can pass a desired predetermined frequency range, unintended falsepositive signal detections can be prevented.

FIG. 3 is a block diagram of an exemplary audio signal detectionalgorithm. At block 301, an input signal can be received by an audiosensor, such as a microphone. At block 302, the input signal can beamplified and passed through a band-pass filter at block 303. At block304, the filtered input signal can be offset and provided to amicrocontroller at block 305. The audio input signal passes from themicrophone to an amplifier and the band-pass filter whose cutofffrequencies are set to limit the signal to the frequency range of atargeted signal. The offset block 304 can be used since many signalprocessing chips operate only with positive voltages. Themicro-controller can determine whether the input signal meets acharacteristic (e.g., temporal characteristic) of an intended targetsignal and/or whether the input signal included one or more of thetargeted signals.

In an aspect, illustrated in FIG. 4A, provided an example apparatususing analog filtering. One or more sensors (e.g., sensor 401 a) can beconfigured to receive one or more input signals via an input jack. Forexample, the modality of the one or more signals can comprise audio,tactile, pressure, IR reflectance, and the like. The one or more inputsignals can be applied to a filter (e.g., band-pass filter) 402. Forexample, rather than responding each time a user touches a switch plate,the band-pass filter 402 can effectively filter out the unintentionaltouches and only respond to an intentional touch. In an aspect, thefilter 402 can be generated by identifying an intentional gesture basedon characteristics of the intentional gesture in the frequency domain,the time domain, or both. An offset can be applied to the filter inputsignal at block 403. The processed input signal can be transmitted to amicrocontroller 404. In another aspect, an input signal does not need tobe processed by the band-pass filter 402 and/or offset sensor 403. Forexample, input signal can be received by sensor 401 b and transmitted tothe microcontroller 404 directly (e.g., via an unfiltered channel). Inan aspect, the microcontroller 404 can comprise one or more gesturedetectors. In an aspect, the microcontroller 404 can not only detect thepresence of an intentional input but can also track a number of inputs(intentional and/or unintentional) produced in succession. For example,one input signal (such as a first tap, a first blink, a first pressurebulb squeeze, or a first small mouth sound) can be used to activate anurse call, while two input signals (e.g., such as a second tap, asecond blink, a second pressure bulb squeeze, or a second small mouthsound) can be used to control an additional device (such as a fan orlight), and three input signals (e.g., such as a third tap, a thirdblink, a third pressure bulb squeeze, or a third small mouth sound) cancontrol yet another one or more devices (such as a TV). This allows auser who can only produce a single gesture to directly control a numberof devices. As an example, a first intentional input can be sent to theoutput interface 405 for control a first device (e.g., nurse call). Asecond intentional input can be sent to the output interface 406 forcontrol a second device (e.g., TV). A third intentional input can besent to the output interface 407 for control a third device (e.g.,computer). In an aspect, any number of output interfaces can beconfigured to control any number of devices.

In an aspect, illustrated in FIG. 4B, provided an example apparatususing digital filtering. As an example, a digital filter 408 can beapplied to the input signals received via sensor 401. The digitallyfiltered input signals can be transmitted to the microcontroller 404. Inan aspect, the microcontroller 404 can comprise one or more gesturedetectors. In an aspect, the microcontroller 404 can not only detect thepresence of an intentional input but can also track a number of inputs(intentional and/or unintentional) produced in succession. In an aspect,a first intentional input can be sent to the output interface 405 forcontrol a first device (e.g., nurse call). A second intentional inputcan be sent to the output interface 406 for control a second device(e.g., TV). A third intentional input can be sent to the outputinterface 407 for control a third device (e.g., computer).

FIG. 5 illustrates the logic of a signal detection algorithm. At block501, an input interface can be sampled to determine if a signal exists.If it is determined at block 502 that no signal exists, then methods canreturn to block 501. If a signal exists, the methods can proceed toblock 503 to determine if a subsequent signal exists. If no subsequentsignal exists, the methods can generate an output at block 504 andreturn to block 501. If an additional signal exists, it can bedetermined whether only one additional signal exists at block 505. Ifonly one additional signal exists, the methods can generate an output atblock 506 and return to block 501. If an additional signal exists, itcan be determined whether only two additional signals exist at block507. If only two additional signals exist, the methods can generate anoutput at block 506 and return to block 501. If an additional signalexists, it can be determined whether only three additional signals existat block 509. If only three additional signals exist, the methods cangenerate an output at block 510 and return to block 501. A variety ofinputs can be utilized and a variety of outputs can be generated at eachsignal processing step.

The present methods and systems can be operational with numerous othergeneral purpose or special purpose computing system environments orconfigurations. Examples of well known computing systems, environments,and/or configurations that can be suitable for use with the systems andmethods comprise, but are not limited to, personal computers, servercomputers, laptop devices, and multiprocessor systems. Additionalexamples comprise set top boxes, programmable consumer electronics,network PCs, minicomputers, mainframe computers, distributed computingenvironments that comprise any of the above systems or devices, and thelike.

In an aspect, illustrated in FIG. 6, provided are methods forcommunication. At block 601, a candidate input can be received. In anaspect, a candidate input can be received from one or more sensors. Asan example, the one or more sensors can comprise one or more of a touchsensor, a pressure sensor (e.g., oral pressure sensor), an opticalreflectance sensor (e.g., infrared reflectance sensor), anelectromyography (EMG) sensor, a light sensor, a proximity detector, anaudio sensor, a mechanical sensor, a capacitance sensor, a camera, andthe like. In an aspect, any type of sensor and any type of output can beutilized. In an aspect, a candidate input can be received from binaryswitches such as push buttons, capacitive touches, squeeze switches, andthe like.

At block 602, the candidate input can be classified as an intentionalinput. In an aspect, classifying the candidate input as an intentionalinput can comprise determining a characteristic of an intentional input,generating a filter based on the characteristic, and applying the filterto the candidate input. In an aspect, the characteristic can be derivedfrom a frequency domain, a time domain, or both. Such time-domain andfrequency-domain characteristics can comprise properties such as a timedomain intensity envelope and/or a frequency domain spectral shape. Asan example, the candidate input can be processed by a signal processor102 to classify a specific stimulus as intentional, as distinguishedfrom noise and unintentional stimuli.

As an example, a characteristic of a tremor can be determined andprocessed to generate a filter. For example, a tremor can generate asignal from about 4 Hz to about 12 Hz, for example a 4 Hz, 5 Hz, 6 Hz, 7Hz, 8 Hz, 9 Hz, 10 Hz, 11 Hz, and/or 12 Hz signal. An intentional tremorcan have a frequency of below about 5 Hz. A low pass filter can beapplied to the signal received from a touch switch to account for thetremors.

As an example, a characteristic of a pressure can be determined andprocessed to generate a filter. For example, the time course of anintentional lip closing gesture and magnitude of the pressure changesassociated with the intentional lip closing gesture can be analyzed. Forexample, the intentional biting down on the bulb will generate asignificantly larger pressure change than the inadvertent rolling of thetongue over the bulb. A filter can be generated to discriminate betweenintentional and unintentional inputs based on particular pressurechanges over a particular time interval. For example, a temporal filtercan distinguish the rapid changes in pressure associated with anintentional oral gesture from the slower changes in pressure associatedwith a non-intentional oral gesture. The temporal filter can alsodistinguish larger magnitude pressure changes from the smaller pressurechanges that may be associated with accidental compression of a sylasticbulb used to detect oral movements.

As another example, a characteristic of an eyelid movement can bedetermined and processed to generate a filter. For example, eye-blinkswitches can be utilized that detects changes in reflected infraredlight that are a consequence of eyelid movements. In an aspect,kinematic analysis of eyelid movements for blink detection can be usedto set temporal cutoffs that only respond to the reflectance changesassociated with the intermediate temporal duration of the intentionalblink/wink.

As another example, a characteristic of a sound can be determined andprocessed to generate a filter. A filter can be generated todiscriminate between the sounds made by small tongue movements andambient noise. Two modes of filtering can be used, specifically, afilter in the frequency domain and a filter in the time domain. Forexample, a candidate signal can be first passed through a band-passfilter to eliminate candidate signals that are not in a known frequencyrange of the intentional gesture sound. However, other environmentalnoises may occur in similar frequency ranges as the intentional gesturesounds, accordingly, a temporal filtering can also be applied. Forexample, background noises can be of random temporal durations, whilethe intentional gesture sounds can be of known temporal durations.Therefore, by ignoring candidate signals that fall within a desiredfrequency range of the intentional gesture sounds and distinguishingtemporal durations longer or shorter than a predetermined durationassociated with an intentional gesture sound, the amount of falsepositive intentional inputs can be further reduced.

At block 603, a signal can be generated in response to the intentionalinput. In an aspect, generating a signal in response to the intentionalinput can comprise activating a nurse call switch. In another aspect,generating a signal in response to the intentional input can comprisecontrolling one or more controlled devices. A controlled device cancomprise one or more of a nurse call switch, a computer, a television, atelephone, a medical device, an application (e.g., iPad applications), aspeech generating device, and the like. In an aspect, the generatedsignal can be used as keyboard commands for communication or controllingother mechanical or computerized outputs. In an aspect, the signal cancomprise an optional visual output. The visual output can be displayedas a menu of instructions and options.

In an aspect, illustrated in FIG. 7, provided are methods forcommunication. At block 701, a candidate input can be received. In anaspect, a candidate input can be received from one or more sensors. Asan example, the one or more sensors can comprise one or more of a touchsensor, a pressure sensor (e.g., oral pressure sensor), an opticalreflectance sensor (e.g., infrared reflectance sensor), anelectromyography (EMG) sensor, a light sensor, a proximity detector, anaudio sensor, a mechanical sensor, a capacitance sensor, a camera, andthe like. In an aspect, any type of sensor and any type of output can beutilized.

At block 702, the candidate input can be classified as an intentionalinput. In an aspect, classifying the candidate input as an intentionalinput can comprise determining a characteristic of an intentional input,generating a filter based on the characteristic, and applying the filterto the candidate input. In an aspect, the characteristic can be derivedfrom a frequency domain, a time domain, or both. Such time-domain andfrequency-domain characteristics can comprise properties such as a timedomain intensity envelope and/or a frequency domain spectral shape.

In an aspect, an intentional input can comprise one or more signals. Forexample, the intentional input can comprise one or more gestures (e.g.,eye blinks) with certain characteristics. As another example, theintentional input can comprise a sequence of gestures (e.g., eye blinkfollowed by a tap). The intentional input can be used to control one ormore devices. As an example, the candidate input can be processed by asignal processor 102 to classify a specific stimulus as intentional, asdistinguished from noise and unintentional stimuli.

As an example, a characteristic of a tremor can be determined andprocessed to generate a filter. For example, a tremor can generate asignal from about 4 Hz to about 12 Hz, for example a 4 Hz, 5 Hz, 6 Hz, 7Hz, 8 Hz, 9 Hz, 10 Hz, 11 Hz, and/or 12 Hz signal. An intentional tremorcan have a frequency of below about 5 Hz. A low pass filter can beapplied to the signal received from a touch switch to account for thetremors.

As an example, a characteristic of a pressure can be determined andprocessed to generate a filter. For example, the time course of anintentional lip closing gesture and magnitude of the pressure changesassociated with the intentional lip closing gesture can be analyzed. Forexample, the intentional biting down on the bulb will generate asignificantly larger pressure change than the inadvertent rolling of thetongue over the bulb. A filter can be generated to discriminate betweenintentional and unintentional inputs based on particular pressurechanges over a particular time interval. For example, a temporal filtercan distinguish the rapid changes in pressure associated with anintentional oral gesture from the slower changes in pressure associatedwith a non-intentional oral gesture. The temporal filter can alsodistinguish larger magnitude pressure changes from the smaller pressurechanges that may be associated with accidental compression of a sylasticbulb used to detect oral movements.

As another example, a characteristic of an eyelid movement can bedetermined and processed to generate a filter. For example, eye-blinkswitches can be utilized that detects changes in reflected infraredlight that are a consequence of eyelid movements. In an aspect,kinematic analysis of eyelid movements for blink detection can be usedto set temporal cutoffs that only respond to the reflectance changesassociated with the intermediate temporal duration of the intentionalblink/wink.

As another example, a characteristic of a sound can be determined andprocessed to generate a filter. A filter can be generated todiscriminate between the sounds made by small tongue movements andambient noise. Two modes of filtering can be used, specifically, afilter in the frequency domain and a filter in the time domain. Forexample, a candidate signal can be first passed through a band-passfilter to eliminate candidate signals that are not in a known frequencyrange of the intentional gesture sound. However, other environmentalnoises may occur in similar frequency ranges as the intentional gesturesounds, accordingly, a temporal filtering can also be applied. Forexample, background noises can be of random temporal durations, whilethe intentional gesture sounds can be of known temporal durations.Therefore, by ignoring candidate signals that fall within a desiredfrequency range of the intentional gesture sounds and distinguishingtemporal durations longer or shorter than a predetermined durationassociated with an intentional gesture sound, the amount of falsepositive intentional inputs can be further reduced.

At block 703, one or more devices associated with the intentional inputcan be determined. For example, a microcontroller 404 can not onlydetect the presence of an intentional input but can also track a numberof inputs (intentional and/or unintentional) produced in succession. Forexample, one input (a first intentional tap, a first intentional blink,a first intentional pressure bulb squeeze, or a first intentional smallmouth sound) can be used to activate a nurse call, while two inputs(e.g., a second intentional tap, a second intentional blink, a secondintentional pressure bulb squeeze, or a second intentional small mouthsound) can be used to control an additional device (e.g., a fan orlight), and three inputs (e.g., a third intentional tap, a thirdintentional blink, a third intentional pressure bulb squeeze, or a thirdintentional small mouth sound) can control yet another additional device(e.g., a TV). In an aspect, this allows a user who can only produce asingle gesture to directly control a number of devices.

In another aspect, a user can control one or more devices by a pluralityof gestures. As an example, a sequence of gestures can be used tocontrol a particular device. For example, an intentional tap followed byan intentional small mouth sound can control a television, while twointentional taps followed by an intentional small mouth sound cancontrol a light. An intentional eye blink and an intentional small mouthsound can control a fan.

At block 704, one or more signals can be generated to control the one ormore devices associated with the intentional input. As an example,controlling the one or more devices can comprise activating a nurse callswitch. In another aspect, generating a signal in response to theintentional input can comprise controlling one or more controlleddevices. A controlled device can comprise one or more of a nurse callswitch, a computer, a television, a telephone, a medical device, anapplication (e.g., an iPad application), a speech generating device, andthe like. In an aspect, the generated signal can be used as keyboardcommands for communication or controlling other mechanical orcomputerized outputs. In an aspect, the one or more signals can comprisean optional visual output. The visual output can be displayed as a menuof instructions and options. As an example, the first signal can begenerated to control a television, a second signal can be generated tocontrol a light, and a third signal can be generated to control an airconditioning system.

In an aspect, illustrated in FIG. 8, provided is an apparatus 800 forcommunication, comprising an input interface 801, configured forreceiving candidate input from one or more sensors, an output interface802, configured for transmitting a signal to a controlled device, amemory 803, configured for storing a filter, and a processor 804,coupled to the input interface 801, the output interface 802, and thememory 803. In an aspect, the processor 804 can be configured to performsteps comprising, classifying the candidate input received by the inputinterface by applying the filter stored in the memory, and providing thesignal to the output interface for transmission to the controlleddevice.

In an aspect, the input interface 801 can comprise one or more of aserial port, a Universal Serial Bus port, a Bluetooth transceiver, an802.xx transceiver, and the like. The output interface 802 can compriseone or more of a serial port, a Universal Serial Bus port, a Bluetoothtransceiver, an 802.xx transceiver, and the like. In a further aspect,the processor 804 can be further configured to perform steps comprisingdetermining a characteristic of an intentional input and generating afilter based on the characteristic. The characteristic can derived fromone or more of a frequency domain and a time domain.

In an aspect, the memory 803 can stored filters and associatedcharacteristics. When a candidate input is received, a filter can beretrieved from the memory 803 according to a characteristic of anintentional input. In an aspect, the characteristic can be derived froma frequency domain, a time domain, or combination thereof.

In an aspect, illustrated in FIG. 9, provided are systems 900 forcommunication. The system 900 can comprise a sensor 901, configured forreceiving one or more candidate inputs, and a communication unit 902coupled to the sensor 901. In an aspect, the communication unit 902 canbe configured to perform steps comprising, receive the one or morecandidate inputs from the sensor 901, classify the one or more candidateinputs as one or more intentional inputs, and generating a signal inresponse to the one or more intentional inputs. The system 900 canfurther comprise a controlled device 903 coupled to the communicationunit 902. In an aspect, the controlled device 903 can be configured toreceive the signal generated by the communication unit 902. Thecontrolled device 903 can comprise one or more of a nurse call switch, acomputer, a television, a telephone, a medical device, and the like. Thesensor 901 can be one or more of a touch sensor, a pressure sensor, aninfrared reflectance sensor, a light sensor, a mechanical sensor, acapacitance sensor, a proximity detector, an audio sensor, a camera, andthe like.

In an aspect, the communication unit 902 can be further configured toperform steps comprising determining a characteristic of the one or moreintentional inputs, generating a filter based on the characteristic, andapplying the filter to the one or more candidate inputs. Thecharacteristic can be derived from a frequency domain, a time domain, orcombination thereof.

One skilled in the art will appreciate that provided is a functionaldescription and that the respective functions can be performed bysoftware, hardware, or a combination of software and hardware. Themethods and systems can comprise the signal processing Software 1006 asillustrated in FIG. 10 and described below. In one exemplary aspect, themethods and systems can comprise a computer 1001 as illustrated in FIG.10 and described below.

FIG. 10 is a block diagram illustrating an exemplary operatingenvironment for performing the disclosed methods. This exemplaryoperating environment is only an example of an operating environment andis not intended to suggest any limitation as to the scope of use orfunctionality of operating environment architecture. Neither should theoperating environment be interpreted as having any dependency orrequirement relating to any one or combination of components illustratedin the exemplary operating environment.

The present methods and systems can be operational with numerous othergeneral purpose or special purpose computing system environments orconfigurations. Examples of well known computing systems, environments,and/or configurations that can be suitable for use with the systems andmethods comprise, but are not limited to, personal computers, servercomputers, laptop devices, and multiprocessor systems. Additionalexamples comprise set top boxes, programmable consumer electronics,network PCs, minicomputers, mainframe computers, distributed computingenvironments that comprise any of the above systems or devices, and thelike.

The processing of the disclosed methods and systems can be performed bysoftware components. The disclosed systems and methods can be describedin the general context of computer-executable instructions, such asprogram modules, being executed by one or more computers or otherdevices. Generally, program modules comprise computer code, routines,programs, objects, components, data structures, etc. that performparticular tasks or implement particular abstract data types. Thedisclosed methods can also be practiced in grid-based and distributedcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules can be located inboth local and remote computer storage media including memory storagedevices.

Further, one skilled in the art will appreciate that the systems andmethods disclosed herein can be implemented via a general-purposecomputing device in the form of a computer 1001. The components of thecomputer 1001 can comprise, but are not limited to, one or moreprocessors or processing units 1003, a system memory 1012, and a systembus 1013 that couples various system components including the processor1003 to the system memory 1012. In the case of multiple processing units1003, the system can utilize parallel computing.

The system bus 1013 represents one or more of several possible types ofbus structures, including a memory bus or memory controller, aperipheral bus, an accelerated graphics port, and a processor or localbus using any of a variety of bus architectures. By way of example, sucharchitectures can comprise an Industry Standard Architecture (ISA) bus,a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, aVideo Electronics Standards Association (VESA) local bus, an AcceleratedGraphics Port (AGP) bus, and a Peripheral Component Interconnects (PCI),a PCI-Express bus, a Personal Computer Memory Card Industry Association(PCMCIA), Universal Serial Bus (USB) and the like. The bus 1013, and allbuses specified in this description can also be implemented over a wiredor wireless network connection and each of the subsystems, including theprocessor 1003, a mass storage device 1004, an operating system 1005,signal processing software 1006, signal data 1007, a network adapter1008, system memory 1012, an Input/Output Interface 1010, a displayadapter 1009, a display device 1011, and a human machine interface 1002,can be contained within one or more remote computing devices 1014 a,b,cat physically separate locations, connected through buses of this form,in effect implementing a fully distributed system.

The computer 1001 typically comprises a variety of computer readablemedia. Exemplary readable media can be any available media that isaccessible by the computer 1001 and comprises, for example and not meantto be limiting, both volatile and non-volatile media, removable andnon-removable media. The system memory 1012 comprises computer readablemedia in the form of volatile memory, such as random access memory(RAM), and/or non-volatile memory, such as read only memory (ROM). Thesystem memory 1012 typically contains data such as signal data 1007and/or program modules such as operating system 905 and signalprocessing software 1006 that are immediately accessible to and/or arepresently operated on by the processing unit 1003.

In another aspect, the computer 1001 can also comprise otherremovable/non-removable, volatile/non-volatile computer storage media.By way of example, FIG. 10 illustrates a mass storage device 1004 whichcan provide non-volatile storage of computer code, computer readableinstructions, data structures, program modules, and other data for thecomputer 1001. For example and not meant to be limiting, a mass storagedevice 1004 can be a hard disk, a removable magnetic disk, a removableoptical disk, magnetic cassettes or other magnetic storage devices,flash memory cards, CD-ROM, digital versatile disks (DVD) or otheroptical storage, random access memories (RAM), read only memories (ROM),electrically erasable programmable read-only memory (EEPROM), and thelike.

Optionally, any number of program modules can be stored on the massstorage device 1004, including by way of example, an operating system1005 and signal processing software 1006. Each of the operating system1005 and signal processing software 1006 (or some combination thereof)can comprise elements of the programming and the signal processingsoftware 1006. Signal data 1007 can also be stored on the mass storagedevice 1004. Signal data 1007 can be stored in any of one or moredatabases known in the art. Examples of such databases comprise, DB2®,Microsoft® Access, Microsoft® SQL Server, Oracle®, mySQL, PostgreSQL,and the like. The databases can be centralized or distributed acrossmultiple systems.

In another aspect, the user can enter commands and information into thecomputer 1001 via an input device (not shown). Examples of such inputdevices comprise, but are not limited to, a keyboard, pointing device(e.g., a “mouse”), a microphone, a joystick, a scanner, tactile inputdevices such as gloves, and other body coverings, and the like These andother input devices can be connected to the processing unit 1003 via ahuman machine interface 1002 that is coupled to the system bus 1013, butcan be connected by other interface and bus structures, such as aparallel port, game port, an IEEE 1394 Port (also known as a Firewireport), a serial port, or a universal serial bus (USB).

In yet another aspect, a display device 1011 can also be connected tothe system bus 1013 via an interface, such as a display adapter 1009. Itis contemplated that the computer 1001 can have more than one displayadapter 1009 and the computer 1001 can have more than one display device1011. For example, a display device can be a monitor, an LCD (LiquidCrystal Display), or a projector. In addition to the display device1011, other output peripheral devices can comprise components such asspeakers (not shown) and a printer (not shown) which can be connected tothe computer 1001 via Input/Output Interface 1010. Any step and/orresult of the methods can be output in any form to an output device.Such output can be any form of visual representation, including, but notlimited to, textual, graphical, animation, audio, tactile, and the like.The display 1011 and computer 1001 can be part of one device, orseparate devices.

One or more sensors 1016 a-e can be configured to provide input tocomputer 1001 through the input/output interface 1010 and/or the networkadapter 1008. The computer 1001 can receive inputs from sensors directlyconnected to the computer 1001 and through the network 1015.

The computer 1001 can operate in a networked environment using logicalconnections to one or more remote computing devices 1014 a,b,c. By wayof example, a remote computing device can be a personal computer,portable computer, smartphone, a server, a router, a network computer, apeer device or other common network node, and so on. Logical connectionsbetween the computer 1001 and a remote computing device 1014 a,b,c canbe made via a network 1015, such as a local area network (LAN) and/or ageneral wide area network (WAN). Such network connections can be througha network adapter 1008. A network adapter 1008 can be implemented inboth wired and wireless environments. Such networking environments areconventional and commonplace in dwellings, offices, enterprise-widecomputer networks, intranets, and the Internet.

For purposes of illustration, application programs and other executableprogram components such as the operating system 1005 are illustratedherein as discrete blocks, although it is recognized that such programsand components reside at various times in different storage componentsof the computing device 1001, and are executed by the data processor(s)of the computer. An implementation of signal processing software 1006can be stored on or transmitted across some form of computer readablemedia. Any of the disclosed methods can be performed by computerreadable instructions embodied on computer readable media. Computerreadable media can be any available media that can be accessed by acomputer. By way of example and not meant to be limiting, computerreadable media can comprise “computer storage media” and “communicationsmedia.” “Computer storage media” comprise volatile and non-volatile,removable and non-removable media implemented in any methods ortechnology for storage of information such as computer readableinstructions, data structures, program modules, or other data. Exemplarycomputer storage media comprises, but is not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium which can be used to store the desired informationand which can be accessed by a computer.

The methods and systems can employ Artificial Intelligence techniquessuch as machine learning and iterative learning. Examples of suchtechniques include, but are not limited to, expert systems, case basedreasoning, Bayesian networks, behavior based AI, neural networks, fuzzysystems, evolutionary computation (e.g. genetic algorithms), swarmintelligence (e.g. ant algorithms), and hybrid intelligent systems (e.g.Expert inference rules generated through a neural network or productionrules from statistical learning).

The following examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how thedevices and/or methods claimed herein are made and used, and areintended to be purely exemplary and are not intended to limit the scopeof the methods and systems

EXAMPLES

In an aspect, the present methods and systems can be implemented via anexample apparatus illustrated in FIG. 11-FIG. 21 and described infurther detail herein. The apparatus can comprise the Noddle™ developedby Voxello. The apparatus can be configured to specifically address theneeds of patients who can not generate the movement or force necessaryto use existing switch technologies. The apparatus can be configured fora user with limited physical abilities. For example, the apparatus canallow the user to utilize whatever type of sensor that is compatiblewith the user's physical capabilities. The apparatus can allow users whocan only generate a single physical gesture to control multiple devices.This functionality is useful, for instance, for a user who can onlyblink one eye to be able to independently and simultaneously control anurse call, television, fan and a speech generating device. The exampleapparatus can perform this functionality based on counting the number oftimes the user produces a gesture within a specified time window.

In an aspect, the apparatus can be configured to detect the smallestintentional gestures (e.g., tongue clicks, finger taps, eye blinks,applying minimal force to a low pressure sensing bulb). The apparatuscan be configured to allow a patient, with a single switch, to controlmultiple devices, such as existing nurse call systems, speech-generatingdevices (SGD), patient controlled analgesia pumps, bed controls,telecommunication devices, environmental control systems, entertainmentsystems, and/or the like.

In an aspect, the apparatus can be configured to accept a range ofsensors (e.g., Noddle-mic™, Noddle-touch™, and many 3^(rd) partyswitches) that can transduce whatever intentional gesture a patient canproduce. The apparatus can be configured to use a gesture detectionalgorithm (e.g., as described herein) that filters out background noiseand patients' unintentional gestures. Depending on whether a singlegesture or sequence of gestures is detected, the apparatus can controlat least three output devices. For example, the apparatus cancommunicate with the output devices via physical network links (e.g.,serial or network communication) and/or wireless network links (e.g.,via Bluetooth, WiFi, DEQ, Z-wave, or possibly new wireless technology inthe future). For example, one intentional tongue click could activatethe nurse call system, while two and three successive tongue clicks canbe used to control a SGD (e.g., using the two-switch scanning mode).Therefore, an intensive care patient who cannot move or speak can usethe apparatus to contact a nurse and also use a speech-generating deviceto communicate about pain or respiratory distress. Finally, theadvantage of the apparatus over other “single” switches on the market isthat patients would be able to take advantage of a “two-switch” scanningmode that allows them to enhance their communication rate by reducingthe number of gestures needed to get to the desired message. Intwo-switch scanning the patient can move through a set of communicationoptions by activating one switch and can then select to output an optionby activating a second switch. For example, an output command (e.g., orsignal) can be selected, and then the output device (e.g., or outputport) can be selected. As another example, an output device (e.g., oroutput port) can be selected, and then an output command can be selectedto output to the selected output device. The available commands forselection can be determined (e.g., or vary) based on the selected outputdevice. The available output devices for selection can be determined(e.g., or vary) based on the selected output command.

FIG. 11A-FIG. 11B show multiple views of an example apparatus. FIG. 11Ashows a top-down perspective view of the apparatus 1100 and a clamp1102. The clamp 1102 can comprise a pole clamp configured to mount theapparatus to a structure, such as a pole used for administering IVfluids. FIG. 11B shows a bottom-up perspective view of the apparatus1100 and the clamp 1102. FIG. 11C shows a side-view of the apparatus1100 and the clamp 1102. FIG. 11D shows another side-view of theapparatus 1100 and the clamp 1102.

FIG. 12A-FIG. 12D illustrate some mounting options of sensors (e.g.,Noddle-mic™ and Noddle-touch™ sensors) coupled with the apparatus.Example sensors can be mounted on a brace (e.g., a Miami-J collar), avent line, bedding and/or the like. FIG. 12A shows a sensor mounted on avent line. FIG. 12B shows a sensor mounted on a brace. FIG. 12C shows asensor mounted on a brace. FIG. 12D shows a sensor mounted on bedding.

FIG. 13A illustrates an example apparatus with an IV pole mounted speechgenerating device (e.g., Noddle-chat™) and customized mounting device(e.g., Noddle-arm™) mounted on an IV pole. The mounting device allows adisplay to be provided to a user for easier control of multiple outputdevices. FIG. 13B illustrates an example user interface provided by thedisplay. FIG. 13C shows another view of the mounting device and displaydevice. The mounting device is attached to an IV pole via a clamp.

In an aspect, the apparatus can be used without calibration and caneffectively be a “plug-and-play” device. The apparatus can be configuredto automatically sense the type of sensor being used and apply theappropriate gesture detection algorithm. Since the apparatus iscompatible with existing nurse call systems and speech-generatingdevices, the apparatus can be used in hospital and/or nursing homeenvironments. The apparatus can be used with eye-tracking enabled SGDs.For example, patients with Amyotrophic Lateral Sclerosis (ALS), andother “locked in syndromes” can use the apparatus for communication. Theprimary obstacles to using eye trackers in acute care facilities involvecalibrating the eye trackers, positioning the device at the bedside, andthe added strain of having to maintain fixation to make a selection.Using the example apparatus would eliminate the added strain forpatients who are able to use shift their gaze and use eye trackers.

The following provides, in more detail, example technical specificationsfor the apparatus. FIG. 14 is a block diagram illustrating an exampleapparatus 1400. The apparatus 1400 can be configured to receive inputfrom wired sensors 1402. The apparatus 1400 can process that input andprovide wired and/or wireless signals via a wireless output 1404 and/ora wired output 1406.

In an aspect, the apparatus 1400 can comprise a sensor recognition unit1408 (e.g., or sensor recognition switch). As illustrated in more detailin FIG. 16, The sensor recognition unit 1408 can be configured todetermine a type of the wired sensor 1402. The type of sensor (e.g., orinformation indicative of the type) can be provided to a processing unit1412, which can determine whether input signals are intentional, whethermultiple signals are intended as a single gesture, and/or otherinformation based on the type of the sensor. The sensor recognition unit1408 can provide the input signal to a filter 1410. The filter 1410 canfilter out unintentional signals as described further herein. Forexample, the filter 1410 can filter (e.g., block, discard, ignore)repetitive signals above or below a frequency. The filter 1410 canfilter signals that do not have expected characteristics (e.g., in thetime domain or frequency domain). The sensor recognition unit 1408 canalso provide input signals to the processing unit 1412. In someimplementations, the input signals can be provided to the filter 1410and/or the processing unit 1410 without passing through the sensor.

The apparatus 1400 can be battery operated and/or receive power fromother power sources. The apparatus 1400 can comprise a power managementsystem 1414. The power management system 1414 can be configured todeliver, manage, conserve and/or the like power throughout the apparatus1400. The apparatus 1400 can comprise a transformer 1416 electricallycoupled to the power management system 1414. For example, thetransformer 1416 can comprise a direct current transformer configured totransform an alternating current source to a direct current. In anaspect, the apparatus 1400 can comprise a one or more status indicatorsystems 1418 as described further herein.

As explained further herein, the processing unit 1412 can be configuredto manage one or more of the components of the apparatus 1400. Theprocessing unit 1412 can be configured to determine output signals andselect output devices to receive output signals. For example, theprocessing unit 1412 can determine the output signals based on a numberof input signals, frequency of input signals, signal characteristics(e.g., amplitude, frequency, voltage, pattern), which sensors the inputsignals are received from, time in between the input signals, time theinput signals are received (e.g., and how such timing corresponds toinformation indicated and/or shown on a display), and/or the like.

FIG. 15 is a block diagram illustrating another example apparatus 1500.In an aspect, the apparatus 1500 can comprise one or more of thecomponents of the apparatus 1400 of FIG. 14. The apparatus 1500 can beconfigured to receive input from one or more wireless sensors. In thisimplementation, the apparatus 1500 can be configured to accept inputfrom a wireless receiver 1502 communicatively coupled (e.g., paired)with one or more wireless sensors 1504.

In an aspect, the apparatus 1500 can detect an intentional gesture viaone of the sensors based on the correct identification of the sensor(s)being used with the apparatus 1500. The apparatus 1500 can receive inputfrom a single sensor or multiple sensors. For example, The apparatus1500 can receive input (e.g., input signals) from an acoustic microphone(e.g., Noddle-mic™), a proximity/capacitance sensor (e.g.,Noddle-touch™), a pressure sensor (e.g., Noddle-bulb™), an IRreflectance sensor (e.g., Noddle-wink™), and/or any other appropriatesensor.

As an illustration, the acoustic microphone can be configured to respondto small intentional tongue clicks that even intubated patients are ableto make. The a proximity/capacitance sensor can function as a proximityswitch (e.g., responds to a change in capacitance that results by somepart of the users body coming in proximity to the sensor) and so candetect small low force movements. The pressure sensor can be activatedby compression of a small bulb by the user. The IR reflectance sensorcan be activated by an eye blink/wink or by any part of the users bodythat can alter the IR reflectance beam. Use of a camera and arecognition algorithm to detect head movement or some other gesture canalso be used by converting a position change signal into a switchsignal.

FIG. 16 is a block diagram of an apparatus illustrating aspects of anexample sensor recognition switch. In an aspect, the apparatus can beconfigured to automatically detect the type of sensor being used. Asshown in FIG. 16, the apparatus can comprise a sensor recognition switch1408. The sensor recognition switch 1408 can be configured to recognizea sensor and/or a type of the sensor. The sensor recognition switch 1408can determine a specific sensor and/or type of sensor (e.g., coupled tothe apparatus, providing signals to the apparatus, in range of theapparatus). For example, the sensor recognition switch 1408 can beconfigured to determine a unique signal voltage produced by a sensorand/or type of sensor. The sensor recognition switch 1408 can determinea resistance value in a parallel input line 1602 that is unique for eachsensor. As explained further herein, an additional resistance value(e.g., unique to each sensor, unique to each type of sensor) can bebuilt-in or added to the sensor that would indicate the gesture timingthreshold to be used in the gesture detection algorithm.

In an aspect, the sensor recognition switch 1408 can be configured todetect gestures as a function of the user's physical state. For example,a user in a first physical state can make gestures with a first speed,frequency, force, and/or the like. A user in a second physical state canmake gestures with a second speed, frequency, force, and/or the like.The sensor recognition switch 1408 can be configured to determinewhether gestures are intentional based on which portion of a user ismaking the gesture, a characteristic (e.g., size, strength, mobility,movement range) of the portion of the user is making the gesture, and/orthe like. For example, the sensor recognition switch 1408 can beconfigured to determine whether a gesture of a limb (e.g., arm, leg) isintentional based on a first force, frequency, speed, and/or the like.The sensor recognition switch 1408 can be configured to determinewhether a gesture of an finger, eye, eyelid, and/or the like isintentional based on a second force, frequency, speed, and/or the like.

In an aspect, different types of sensor can be associated with differenttiming thresholds. For example, the sensors can have fixedcharacteristics (e.g., voltage, resistance). Thus, the characteristicscan be associated with specific timing thresholds. As another example,the sensors can be modified by a user (e.g., via hardware and/orsoftware setting). For example, a sensor can comprise a switch to selectdifferent resistance values. Accordingly, the user can set the timingthreshold by adjusting the resistance value of the sensor. Where thesensor characteristic is fixed, the user can adjust the timing thresholdby using a different sensor or sensor type. In some implementations, aninterface of the apparatus can be accessed to adjust whichcharacteristics are associated with which timing thresholds.

In an aspect, the sensor recognition switch 1408 can be configured todetermine the type of sensor based on information from the sensor. Theinformation can comprise a code. In the case of wireless sensors, aunique wireless code assigned to a particular type of sensor can beprovided by the sensor to the apparatus. The unique code can be used toindicate, determine, and/or the like the gesture timing threshold for aspecific sensor. A code can also be provided by wired sensor foridentification of the sensor and/or type of sensor.

In an aspect, the sensor recognition switch 1408 can be configured todetermine the type of sensor based on hardware and/or softwarecharacteristics associated with the sensor. For example, a sensor can becoupled to the apparatus via at least two input lines. A first inputline 1604 can provide sensor output from a user. The second input line1602 can be in parallel with the first input line 1602. The second inputline 1602 can comprise a resistor. The apparatus can determine theresistance, voltage drop and/or other characteristic indicative of thesensor based on the first input line 1604 and/or second input line 1602.For example, a signal received from the second input line 1602 can becompared to a power output line 1606 (e.g., of the sensor, a power linefrom the apparatus to the sensor, a power line of a power sourcereceived by the apparatus and/or sensor) to determine the signal (e.g.,or information, resistance, value) produced by the resistor network1608. A voltage difference or other difference in characteristics of thesignals from the first input line 1604 and power output line 1606 can bedetermined to identify the sensor and/or type of sensor.

In another aspect, an input signal sensing algorithm can be used todetermine the sensor and/or type of the sensor. For example, sensorsand/or types of sensors can be associated with correspondingcharacteristics, such as signal voltages, signal patterns, signalfrequencies, signal waveforms (e.g., sinusoidal, square, triangle),and/or the like.

FIG. 17 illustrates an example processing unit 1412 of the apparatus.The processing unit 1412 can comprise a sensor detection unit 1702. Thesensor detection unit 1702 can be configured to detect a sensor and/ortype of sensor coupled (e.g., communicatively coupled) to the apparatus.For example, the sensor detection unit 1702 can comprise and/or managethe sensor recognition switch 1408. The processing unit 1412 cancomprise a gesture detection unit 1704 configured to classify inputsignals as intentional or unintentional gestures as explained herein.The processing unit 1412 can comprise a gesture counter unit 1706configured to count gestures as explained herein. The processing unit1412 can comprise an output selection unit 1708 configured to select anoutput based on the number of gestures counted by the gesture counterunit 1706. The output selection unit 1708 can select one or morewireless outputs 1404 and/or wired outputs 1406. The processing unit1412 can also comprise a status indicator output configured to indicatethe status of the processing unit 1412.

When the apparatus is used with a single sensor, the apparatus can allowthe user to effectively have the equivalent of at least three switchesthat can be linked to a range of devices. This is accomplished by thegesture counting algorithm. For example, the first detected gesture caninitiate a counting window. The counting window can define aninter-gesture interval (IGI). For an additional gesture to be added tothe count a minimal IGI must be exceeded. In addition, if a maximum IGIis exceeded, then the next signal received can be determined as a uniquegesture rather than one of a series of related gestures (e.g., or aseries of signals related to a signal gesture). An illustration of thegesture counting algorithm using a single sensor is as follows. If themaximum IGI is exceeded without additional detected gesture, then theapparatus will selected (e.g., set, determine) output 1. If a secondgesture is detected within the IGI and then the maximum IGI is exceededwithout an additional gesture, then the apparatus can selected output 2.If a third gesture is detected within the IGI and then the maximum IGIis exceeded without an additional gesture, then the apparatus can selectoutput 3. If a fourth gesture is detected within the IGI, then theapparatus can determine not to select any output. This last option isincluded to allow the user to abort if he/she wishes to not have anyoutput set.

Table 1 illustrates an example relationship between the number ofcounted gestures and the output selected when only a single sensor isused.

TABLE 1 Number of Gestures Output Selected 1 1 2 2 3 3 4 (no output) -functions to abort sequence

Table 2 illustrates the relationship between the number of gesturescounted and the output selected when more than one sensor is used. As anillustration, multiple sensors can be used to select outputs as follows.If the maximum IGI is exceeded without additional detected gesture andif the gesture was detected by sensor A, the apparatus can selectoutput 1. If the maximum IGI is exceeded achieved without additionaldetected gesture and if the gesture was detected by sensor B, theapparatus can select (e.g., determine, set) output 2. If a secondgesture is detected from the same sensor (e.g. sensor A) within the IGIand then the maximum IG is exceeded without an additional gesture, thenthe apparatus can select output 3. If a second gesture is detected fromthe same sensor (e.g. sensor B) within the IGI and then the maximum IGIis exceeded without an additional gesture, then the apparatus can selectoutput 4. If a second gesture is detected from a different sensor (e.g.sensor A followed by sensor B) within the IGI and then the maximum IGIis exceeded without an additional gesture, then the apparatus can selectoutput 5. If a second gesture is detected from a different sensor (e.g.sensor B followed by sensor A) within the IGI and then the maximum IGIis exceeded without an additional gesture, then the apparatus can selectoutput 6. If three gestures are detected within the IGI, regardless ofwhich sensors are activated, then the apparatus can select no output.Any three gesture sequence allows the user to abort if he/she wishes tonot have any output set. It should be understood that the apparatus canbe configured to count longer strings of gestures from one or moresensors thereby allowing for control of a larger number of outputs.

TABLE 2 Second Third Gesture First Gesture Detected Gesture DetectedDetected Output Sensor ID Sensor ID Sensor ID Selected A — — 1 B — — 2 AA — 3 B B — 4 A B — 5 B A — 6 A A A or B (no output) B B A or B (nooutput) A B A or B (no output) B A A or B (no output)

As illustrated in FIG. 14, FIG. 15, and FIG. 17, the apparatus canprovide both hardwired and wireless outputs. The hardwired outputs canbe isolated relay outputs (e.g., an electrically operated switch). Theisolated relay outputs can be configured as either normally open ornormally closed. In an aspect, the apparatus can provide output signalscomprising commands, characters (e.g., keyboard characters), functionparameters, device settings. For example, the output can be in the formof a set (e.g., string, array, formatted data structure) of characters(e.g., keyboard characters). The apparatus also can provide the outputvia a serial port (e.g., USB port), wireless transceiver, networkinterface, and/or the like. Example commands can comprise a power on,power off, volume up, volume down, channel up, channel down, pause,play, fast forward, rewind, mute, open application, close application,like command, bookmark command, nurse call command, dial number,temperature setting, temperature up, temperature down, light on, lightoff, medication request, indicate an increase in pain level, indicate adecrease in pain level, changing feeling status, and/or the like. Asanother example, the command can comprise any language, speech, text,audio and/or the like generated by a user by issuing commands (e.g.,selecting letters, words, or otherwise generating output) to a speechgeneration device. Through a speech generation device coupled to theapparatus there is almost no limit as to what the patient cancommunicate depending on how the device is programmed and set up.

In an aspect, the processing unit 1412 can be configured to control thestatus indicator system 1418 which provides the user feedback about thestatus of the device hardware, about the detection of intentionalgestures, and/or other useful information. For example, the statusindicator system 1418 can comprise a power indicator (e.g., LED powerindicator). The power indicator can provide a steady illumination (e.g.,green light) when the device is on. The status indicator system 1418 cancomprise a charging indicator. The charging indicator can provide steadyillumination when a battery of the apparatus is charging. The chargingindicator can flash to indicate a battery charge error. When thecharging indicator is not illuminated, the charge is complete and/or theapparatus is not charging the battery. The status indicator system 1418can comprise a low battery indicator. The low battery indicator canflash (e.g., flash red) when the battery is low. A noise can also beemitted (e.g., pulsing beep). The status indicator system 1418 cancomprise a sensor connection indicator. When a sensor is not coupled tothe apparatus, a signal (e.g., red illumination) can be provided by thesensor connection indicator. The status indicator system 1418 cancomprise a gesture detection indicator. The gesture detection indicatorcan provide a number of flashes (e.g., blue flashes) corresponding to anumber of detected gestures. The status indicator system 1418 cancomprise an output selection indicator. The output selection indicatorcan provide a number of flashes (e.g., green flashes) indicator a numberof the selected output.

FIG. 18 illustrates an example power management system 1414. Theapparatus can be powered from either the electrical mains using a DCpower adapter (e.g., DC transformer 1416) or secondarily by an internalrechargeable battery 1801. The power management system 1414 can comprisea charge management system 1802 configured to prevent over charging ofthe internal battery 1801. The power management system 1414 also cancomprise safety features like a thermal cutoff element 1804 to precludethe possibility of overheating and the risks of fire. The powermanagement system 1414 can also comprise a circuit protection element1806, a voltage regulator 1808, a charge level indicator 1810, and/orother elements related to power management.

FIG. 19 is a flow chart illustrating an example method 1900 for managinga device. At step 1901, a first plurality of candidate inputs can bereceived from a first sensor. The first plurality of candidate inputscan comprise input signals. The first plurality of candidate inputsignals can be received via wired and/or wireless communication links.

At step 1902, a type of the first sensor can be determined. The type ofthe first sensor can be determined based on a voltage level of a signalreceived from the first sensor. In another aspect, determining the typeof the first sense can comprise determining an electrical resistancevalue of a connection with the first sensor. The type of the firstsensor can be determined based on the electrical resistance value.

At step 1903, a first timing threshold can be determined based on thetype of the first sensor. The first timing threshold can comprise aminimum duration of time between intentional inputs. For example,different types of sensors can be associated with different timingthresholds. The timing thresholds can be accessed in a data structure,database, and/or the like.

At step 1904, one or more of the first plurality of candidate inputs canbe classified as intentional inputs based on the first timing threshold.For example, a difference in time can be determined between a first timeof receiving a first candidate input and a second time of receiving acandidate input prior (e.g., the immediately prior) to the firstcandidate input. If the difference is less than the first timingthreshold, then the first candidate signal can be classified asunintentional. If the difference is greater than the first timingthreshold, then the first candidate signal can be classified asintentional.

At step 1905, an output signal can be provided to a device based on theone or more of the first plurality of candidate inputs classified asintentional inputs. The device can be selected based on a number of thefirst plurality of candidate inputs classified as intentional inputs.For example, step 1905 can comprise counting a number of the one or moreof the first plurality of candidate inputs classified as intentionalinputs. The device can be selected based on the number.

In another aspect, the method 1900 can further comprise receiving asecond plurality of candidate inputs from a second sensor. A type of thesecond sensor can be determined. A second timing threshold can bedetermined based on the type of the second sensor. The device can beselected for receiving the output signal based on a combination of anumber of the first plurality of inputs classified as intentional inputsand a number of the second plurality of inputs classified as intentionalinputs.

FIG. 20 is a flow chart illustrating an example method 2000 forrecognizing a gesture. At step 2001, a first input signal can bereceived. The first input signal can be received from a first sensor.The first sensor can comprise touch sensor, a pressure sensor, amechanical sensor, an optical reflectance sensor, an infraredreflectance sensor, a light sensor, a proximity detector, a capacitancesensor, an audio sensor, and a camera. As a further example, the firstsensor can comprise an infrared reflectance sensor, a pressure bulbsensor, a proximity capacitance sensor, an acoustic microphone sensor,and/or any other appropriate sensor. The first sensor can be configuredto provide only one type of signal or multiple types of signals (e.g.,having variable voltages, frequencies, currents, and/or the like). Forexample, the first sensor can provide a single type of signal having aset characteristic (e.g., voltage, frequency, amplitude, pattern, and/orthe like). In another aspect, the characteristics of the signal can varybased on the force applied by the user to the first sensor and/or othersettings that the user can modify.

At step 2002, a second input signal can be received after the firstinput signal. The second input signal can be received from the firstsensor and/or a second sensor. The second sensor can comprise a touchsensor, a pressure sensor, a mechanical sensor, an optical reflectancesensor, an infrared reflectance sensor, a light sensor, a proximitydetector, a capacitance sensor, an audio sensor, and a camera. As afurther example, the second sensor can comprise an infrared reflectancesensor, a pressure bulb sensor, a proximity capacitance sensor, anacoustic microphone sensor, and/or any other appropriate sensor. Thesecond sensor can be configured to provide only one type of signal ormultiple types of signals (e.g., having variable voltages, frequencies,currents, and/or the like). For example, the second sensor can provide asingle type of signal having a set characteristic (e.g., voltage,frequency, amplitude, pattern, and/or the like). In another aspect, thecharacteristics of the second signal can vary based on the force appliedby the user to the second sensor and/or other settings that the user canmodify. The characteristics of the second signal can be different thanthe characteristics of the first signal.

At step 2003, the first input signal and/or the second input signal canbe classified as intentional signals. For example, the first inputsignal can be classified based on a first characteristic of the firstinput signal. The first characteristic can be a time domaincharacteristic, a frequency domain characteristic, and/or the like. Forexample, one or more filters (e.g., hi-pass filter, low pass filter) canbe applied to the first input signal. The second input signal can beclassified based on a second characteristic of the second input signal.The second characteristic can be a time domain characteristic, afrequency domain characteristic, and/or the like. For example, one ormore filters (e.g., hi-pass filter, low pass filter) can be applied tothe second input signal.

At step 2004, timing information indicative of a time difference betweenreceiving the first input signal and receiving the second input signalcan be determined. For example, a first time indicative of the firstinput signal (e.g., a time when the first input signal is received) canbe determined. A second time indicative of the second input signal canbe determined (e.g., a time when the second input signal is received).The timing information can comprise a time difference between the firsttime and the second time (e.g., a length or duration of time between thefirst time and the second time.

At step 2005, a determination can be made on whether the first inputsignal and the second input signal are relevant to a single command ormultiple commands based on the timing information. For example, step2005 can comprise comparing the timing information to a gesture timewindow. The gesture time window can comprise an maximum amount of timebefore two input signals (e.g., received in succession) are interpretedas relating to different gestures. The gesture time window can bespecified by a user providing the first input signal and the secondinput signal. If the time difference is less than the gesture timewindow then the first input signal and the second input signal aredetermined to be relevant to a single gesture. If the time difference isgreater than the gesture time window, then the first input signal andthe second input signal can be determined to be relevant to twodifferent gestures. In an aspect, the gesture time window can be basedon a type of the first sensor and/or a type of the second sensor.

In another aspect, the gesture time window can initiated (e.g., start)in response to receiving the first input signal. The gesture time windowcan end after a set time. For example, if the end of the gesture timewindow is after the second time, then the first input signal and thesecond input signal can be determined to be relevant to the singlegesture. If the end of the gesture time window is before the secondtime, then the first input signal and the second input signal can bedetermined to be relevant to two separate gestures.

At step 2006, one or more output signals can be provided based on thedetermination of whether the first input signal and the second inputsignal are relevant to a single gesture or multiple gestures. Forexample, the device to provide the one or more output signals to can beselected based on a count of input signals received during the gesturetime window.

FIG. 21 is a flow chart illustrating an example method 2100 forrecognizing a gesture. At step 2101, a first plurality of candidateinputs can be received. The first plurality of candidate inputs can bereceived from one or more sensors, via wired and/or wirelesscommunication links. At step 2102, the first plurality of candidateinputs can be classified as one or more first intentional inputs. Forexample, time domain and/or frequency domain characteristics of thefirst plurality of candidate inputs can be analyzed to determine whichof the first plurality of candidate inputs are intentional as describedfurther herein.

At step 2103, a number of the one or more first intentional inputs canbe counted. For example, a hardware or software counter can determinethe number. The number can comprise a number counted during a gesturetime window. At step 2104, a target device can be selected based on thenumber of the one or more first intentional inputs. For example, thetarget device can be associated with the number. Each of a plurality ofoutputs can be give an a corresponding number.

At step 2105, a second plurality of candidate inputs can be received.For example, after a target device is selected, a command detection timewindow can begin (e.g., be initiated). During the command detection timewindow, candidate inputs determined as intentional can be used todetermine a command. At step 2106, the second plurality of candidateinputs can be classified as one or more second intentional inputs. Forexample, time domain and/or frequency domain characteristics of thefirst plurality of candidate inputs can be analyzed to determine whichof the first plurality of candidate inputs are intentional as describedfurther herein.

At step 2107, a command for controlling the target device can bedetermined based on the one or more second intentional inputs. Thecommand can comprise a command for an application on the target device.For example, the target device can be associated with and/or support aplurality of commands. The command can be determined based on acharacteristic (e.g., a number, a pattern, a frequency, a voltage) ofthe one or more second intentional inputs. For example, the command canbe associated with a corresponding number (e.g., or othercharacteristic) for the target device (e.g., or an application thereon).The number can be specific to the target device. As an illustration, ifthree intentional inputs are received in the command detection timewindow, then the command associated with the number three can beprovided to the target device.

At step 2108, a signal indicative of the command to the selected targetdevice can be provided in response to the intentional input. The signalcan comprise characters indicative of the command, voltages, signalspatterns, amplitudes and/or other information for identifying thecommand.

While the methods and systems have been described in connection withpreferred embodiments and specific examples, it is not intended that thescope be limited to the particular embodiments set forth, as theembodiments herein are intended in all respects to be illustrativerather than restrictive.

Unless otherwise expressly stated, it is in no way intended that anymethod set forth herein be construed as requiring that its steps beperformed in a specific order. Accordingly, where a method claim doesnot actually recite an order to be followed by its steps or it is nototherwise specifically stated in the claims or descriptions that thesteps are to be limited to a specific order, it is no way intended thatan order be inferred, in any respect. This holds for any possiblenon-express basis for interpretation, including: matters of logic withrespect to arrangement of steps or operational flow; plain meaningderived from grammatical organization or punctuation; the number or typeof embodiments described in the specification.

Throughout this application, various publications are referenced. Thedisclosures of these publications in their entireties are herebyincorporated by reference into this application in order to more fullydescribe the state of the art to which the methods and systems pertain.

It will be apparent to those skilled in the art that variousmodifications and variations can be made without departing from thescope or spirit. Other embodiments will be apparent to those skilled inthe art from consideration of the specification and practice disclosedherein. It is intended that the specification and examples be consideredas exemplary only, with a true scope and spirit being indicated by thefollowing claims.

What is claimed is:
 1. An apparatus comprising: one or more processors;and memory storing processor-executable instructions that, when executedby the one or more processors, cause the apparatus to: receive a firstinput signal from a first sensor configured to detect only a singlegesture; receive a second input signal from the first sensor; classifythe first input signal and the second input signal as intentionalsignals; determine timing information indicative of a time differencebetween receiving the first input signal and receiving the second inputsignal; determine, based on the timing information, whether the firstinput signal and the second input signal are relevant to a singlecommand or multiple commands; select, based on a count of input signalsreceived during a first gesture time window, a device from a pluralityof devices to provide one or more output signals to, wherein each deviceof the plurality of devices is associated with a respective number and anumber of the device matches the count of the input signals; and send,to the device, the one or more output signals based on determiningwhether the first input signal and the second input signal are relevantto the single command or the multiple commands.
 2. The apparatus ofclaim 1, wherein the processor-executable instructions that cause theapparatus to determine whether the first input signal and the secondinput signal are relevant to the single command or the multiple commandscomprise processor-executable instructions that, when executed by theone or more processors, cause the apparatus to: compare the timinginformation to a second gesture time window, wherein the apparatusdetermines that the first input signal and the second input signal arerelevant to a gesture if the time difference is less than the secondgesture time window.
 3. The apparatus of claim 2, wherein the firstgesture time window is defined by the first input signal and the secondinput signal.
 4. The apparatus of claim 1, wherein the apparatusreceives the second input signal received from a second sensor.
 5. Anapparatus comprising: one or more processors; and memory storingprocessor-executable instructions that, when executed by the one or moreprocessors, cause the apparatus to: receive a plurality of candidateinputs from a first sensor configured to detect only a single gesture;classify the plurality of candidate inputs as one or more intentionalinputs; count a number of the one or more intentional inputs; select atarget device of a plurality of devices based on the number of the oneor more intentional inputs, wherein each device of the plurality ofdevices is associated with a respective number and a number of thetarget device matches the number of the one or more intentional inputs;and send a signal to the selected target device in response to theclassified one or more intentional inputs.
 6. The apparatus of claim 5,wherein the processor-executable instructions that cause the apparatusto receive the plurality of candidate inputs compriseprocessor-executable instructions that, when executed by the one or moreprocessors, cause the apparatus to receive an input from a secondsensor.
 7. The apparatus of claim 5, wherein the first sensor comprisesone or more of a touch sensor, a pressure sensor, a mechanical sensor,an optical reflectance sensor, an infrared reflectance sensor, a lightsensor, a proximity detector, a capacitance sensor, an audio sensor, ora camera.
 8. The apparatus of claim 5, wherein the processor-executableinstructions that cause the apparatus to classify the plurality ofcandidate inputs as the one or more intentional inputs compriseprocessor-executable instructions that, when executed by the one or moreprocessors, cause the apparatus to: determine a characteristic of anintentional input; generate a filter based on the characteristic; andapply the filter to one or more of the plurality of candidate inputs. 9.The apparatus of claim 8, wherein the processor-executable instructions,when executed by the one or more processors, further cause the apparatusto derive the characteristic from a frequency domain.
 10. The apparatusof claim 8, wherein the processor-executable instructions, when executedby the one or more processors, further cause the apparatus to derive thecharacteristic from a time domain.
 11. The apparatus of claim 5, whereinthe processor-executable instructions that cause the apparatus to sendthe signal to the selected target device comprise processor-executableinstructions that, when executed by the one or more processors, causethe apparatus to activate one or more of a nurse call switch, acomputer, a television; a fan, a light, a telephone, or a medicaldevice.
 12. The apparatus of claim 5, wherein the processor-executableinstructions that cause the apparatus to send the signal to the selectedtarget device comprise processor-executable instructions that, whenexecuted by the one or more processors, cause the apparatus to controlthe selected target device.
 13. An apparatus comprising: one or moreprocessors; and memory storing processor-executable instructions that,when executed by the one or more processors, cause the apparatus to:receive a first plurality of candidate inputs from a first sensorconfigured to detect only a single gesture; determine a type of thefirst sensor; determine a first timing threshold based on the type ofthe first sensor; classify one or more of the first plurality ofcandidate inputs as intentional inputs based on the first timingthreshold; and send an output signal to a device of a plurality ofdevices based on the one or more of the first plurality of candidateinputs classified as intentional inputs, wherein each device of theplurality of devices is associated with a respective number and a numberof the device matches a number of the first plurality of candidateinputs classified as intentional inputs.
 14. The apparatus of claim 13,wherein the processor-executable instructions, when executed by the oneor more processors, cause the apparatus to determine the type of thefirst sensor based on a voltage level of a signal received from thefirst sensor.
 15. The apparatus of claim 13, wherein theprocessor-executable instructions, when executed by the one or moreprocessors, cause the apparatus to determine the type of the firstsensor based on a code received from the first sensor.
 16. The apparatusof claim 13, wherein the processor-executable instructions, whenexecuted by the one or more processors, further cause the apparatus todetermine an electrical resistance value of a connection with the firstsensor, wherein the type of the first sensor is determined based on theelectrical resistance value.
 17. The apparatus of claim 13, wherein thefirst timing threshold comprises a minimum duration of time betweenintentional inputs.
 18. The apparatus of claim 13, wherein theprocessor-executable instructions that cause the apparatus to send theoutput signal to the device comprise processor-executable instructionsthat, when executed by the one or more processors, cause the apparatusto: count a number of the one or more of the first plurality ofcandidate inputs classified as intentional inputs; and select the devicebased on the number.
 19. The apparatus of claim 13, wherein theprocessor-executable instructions, when executed by the one or moreprocessors, further cause the apparatus to: receive a second pluralityof candidate inputs from a second sensor; determine a type of the secondsensor; and determine a second timing threshold based on the type of thesecond sensor, wherein the device to send the output signal to isselected based on a combination of a number of the first plurality ofcandidate inputs classified as intentional inputs and a number of thesecond plurality of candidate inputs classified as intentional inputs.20. The apparatus of claim 13, further comprising: an input interfaceconfigured to receive the first plurality of candidate inputs; and anoutput interface configured to send the output signal.